Heterogeneous immunoassays such as enzyme-linked immunosorbent assays (ELISA), bead based immunoassays, and protein microarrays are widely used in the biological sciences and medical diagnostic applications. Immunoassays can be sandwich assays, with specific capture antibodies immobilized on a solid support and a specific detection antibody forming a “sandwich” with the target analyte. The detection antibody may be labeled with a detectable label for signal transduction, such as an enzyme, fluorescent dye, fluorescent particle, etc. The detection antibody may also be labeled using an anti-species antibody conjugated with a detectable label. Various permutations of heterogeneous immunoassays such as competitive and indirect immunoassays are also well known in the art.
Quantitative immunoassays generate data that are typically presented as signal intensity versus concentration, and typically have a sigmoidal shape. The flattening of signal at high analyte concentration can result from saturation of available binding sides on the solid surface. A decrease in signal at very high and increasing target analyte concentration is called the hook effect or prozone effect, and is well-described in the literature. In this case, an excess of analyte depletes available detection reagent (e.g., detection antibody) and therefore decreases signal (see FIG. 2). This paradoxical decrease in signal with increasing target concentration is a problem that must be addressed in immunoassay with large dynamic range.
The most common method for dealing with hook effect is to dilute the sample. In many applications, however, the addition of manual or automated sample processing steps is undesirable, particularly for cost and complexity reasons. Minimizing the number and complexity of steps that a user must perform to execute the test will decrease the cost of the test and also improve the results since there will be fewer opportunities for user error. Although methods that characterize the hook effect exist and some of these methods correct for this effect, to date no method has been developed, which combines hook detection and correction in a single, simple measurement.
Multiple methods that provide hook effect detection have been described. In European Patent Application EP 1 361 435 A1, hook effect is detected by the signal from a specific binding substance and a sandwich reaction, and the device automatically performs a sample dilution. In US Patent Application 2003023360 A2, hook effect is detected by performing a sandwich reaction and a competitive assay for the same analyte, and then a manual dilution step must be performed. Another method of reducing the hook effect is to reduce the analyte concentration by adding a ligand compliment such as is described in U.S. Pat. No. 5,089,391 A. The ligand compliment must be removed before performing the immunoassay, which adds an additional assay step. A different approach uses flow cytometry to detect the analyte concentration on a particle such as a bead to measure the hook effect as described in WO 2001063284 A2.
WO 2014106033 A1 describes a multiple sensor device in which two different concentrations of the same immunosensor are used to detect the analyte concentration. An automated processor determines whether the hook effect is present by either comparing the signal sizes from these two immunoassays or by taking the ratio of the signal sizes. The method disclosed in WO 2014106033 A1 thus requires performing two immunoassays. However, this method does not actually correct for the hook effect, it simply detects the presence of the effect.
U.S. Pat. No. 7,858,321 B2 measures the hook effect by performing immunoassays simultaneously in a multiple well plate with multiple domains per well. Two different immunoassays are simultaneously measured: a sandwich immunoassay and a competitive assay for the analyte. As is the case for WO 2014106033 A1, the method of U.S. Pat. No. 7,858,321 B2 does not correct for the hook effect.